Energy-Efficient Buildings ML Research Assistant

CamWebDir; Cambridge; Remote; GBP 29,000 - 36,000; Full time

Job summary

University of Cambridge seeks a Research Assistant (Fixed Term) to develop data-driven and AI-based methods for improving energy efficiency of buildings and reducing carbon footprint. You will work on decarbonising heat in the UK’s existing building stock using data, modelling, and intelligent control.

The role involves building unified data pipelines, analyzing real-time and historical data, and prototyping approaches in a real deployment environment, at Queens’ College Cambridge, in

Qualifications

• Energy systems experience is desirable.
• Familiarity with building data and ML methods is an asset.

Responsibilities

• Develop data-driven and AI-based methods for improving building energy efficiency.
• Create unified datasets and data pipelines from sensors, energy systems, and weather data.
• Develop predictive models for heating/electricity demand and operating costs.
• Prototype and deploy methods in real buildings in collaboration with deployment teams.

Skills

Energy systems

Building simulation

Reinforcement learning

Control

Sensor data

Physics-informed ML

Job description

University of Cambridge seeks a Research Assistant (Fixed Term) to develop data-driven and AI-based methods for improving energy efficiency of buildings and reducing carbon footprint. You will work on decarbonising heat in the UK’s existing building stock using data, modelling, and intelligent control.

The role involves building unified data pipelines, analyzing real-time and historical data, and prototyping approaches in a real deployment environment, at Queens’ College Cambridge, in